Face mask recognition based on object detection

Yuxuan Zhang; Chen Yang; Qiaodan Zhao

doi:10.1117/12.2600460

1 June 2021 Face mask recognition based on object detection

Yuxuan Zhang, Chen Yang, Qiaodan Zhao

Proceedings Volume 11848, International Conference on Signal Image Processing and Communication (ICSIPC 2021); 1184814 (2021) https://doi.org/10.1117/12.2600460
Event: International Conference on Signal Image Processing and Communication (ICSIPC 2021), 2021, Chengdu, China

Abstract

Earlier in 2019, a novel coronavirus pneumonia outbreak occurred in most countries and regions of the world. Thus, judging whether individuals are wearing masks or not has become an important part of entrance inspection in many places. In this paper, object detection in Google Cloud Platform's AutoML is used to implement mask detection. 1,000 from these 2,000 pictures are selected to refine the dataset for training, including 500 faces with masks and 500 faces without masks. After training, the accuracy achieves 94% and the map achieves 97.3%, which can meet the requirements of practical application. What’s more, tflite is used to deploy the model on the edge, to realize the application of the model in the real scenes.

Citation Download Citation

Yuxuan Zhang, Chen Yang, and Qiaodan Zhao "Face mask recognition based on object detection", Proc. SPIE 11848, International Conference on Signal Image Processing and Communication (ICSIPC 2021), 1184814 (1 June 2021); https://doi.org/10.1117/12.2600460

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